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2018 IEEE Region 10 Humanitarian Technology Conference (R10-HTC)最新文献

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R10-HTC 2018 Organizing Committee R10-HTC 2018组委会
Pub Date : 2018-12-01 DOI: 10.1109/r10-htc.2018.8629839
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引用次数: 0
Energy Efficient Adder for Bio-Medical Applications 生物医学应用的节能加法器
Pub Date : 2018-12-01 DOI: 10.1109/R10-HTC.2018.8629810
Srilakshmi Kaza, V. N. T. Alapati, Srinivasa Rao Kunupalli
Recent developments in sensors and novel device structures have opened up many new possibilities in medical field, especially in implantable medical devices. The battery recharge timing places stringent requirements on power consumption by these devices. The design of energy-efficient circuits and systems thus becomes more crucial. Adder is the basic building block for all these devices. In this paper, a 4-bit Brent-Kung adder is implemented with a new adiabatic logic family derived from the PFAL, denoted as modified PFAL or MPFAL and using FinFET device. The performance of the adder circuit is analyzed by comparing the power dissipation and delay with that of static CMOS and PFAL designs. The simulation results indicate reduction in power dissipation of 98% and 96% over static CMOS and PFAL designs. The delay improvement is 24% for MPFAL circuit.
近年来传感器和新型器件结构的发展为医疗领域,特别是植入式医疗器件开辟了许多新的可能性。电池充电时间对这些设备的功耗提出了严格的要求。因此,节能电路和系统的设计变得更加重要。加法器是所有这些设备的基本组成部分。本文采用基于PFAL的新型绝热逻辑族实现了一个4位Brent-Kung加法器,称为改进PFAL或MPFAL,并使用FinFET器件。通过与静态CMOS和PFAL设计的功耗和延迟进行比较,分析了加法器电路的性能。仿真结果表明,与静态CMOS和PFAL设计相比,功耗分别降低98%和96%。MPFAL电路的延迟改善为24%。
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引用次数: 3
R10-HTC 2018 Workshops R10-HTC 2018研讨会
Pub Date : 2018-12-01 DOI: 10.1109/r10-htc.2018.8629813
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引用次数: 0
Comparison of Brain Functional Networks for Subjects with Different Performance 不同表现受试者脑功能网络的比较
Pub Date : 2018-12-01 DOI: 10.1109/R10-HTC.2018.8629822
Kang Wei Thee, H. Nisar
In this study, brain functional networks are compared for different subjects while performing the visual oddball task. The time series electroencephalography (EEG) signals were acquired from 20 healthy subjects during a visual oddball experiment using 128 channels machine with a sampling rate of 250 Hz. The clean data was filtered by finite impulse response (FIR) filter for EEG rhythmic decomposition. Phase Locked Value (PLV) is used to measure all pairwise phase synchronizations of EEG electrodes. Hilbert transform was then applied to the decomposed data to extract instantaneous phases. Graph theory approach is finally used to quantify the functional networks. Results show that target stimuli elicited denser neural activity as compared to non-target stimuli. Subject with higher performance accuracy when performing the oddball task has greater neural activity than the subject with lower accuracy.
本研究比较了不同受试者在执行视觉怪任务时的脑功能网络。采用128通道机器,以250 Hz的采样率采集20名健康受试者的视觉奇球实验时间序列脑电图信号。用有限脉冲响应(FIR)滤波对干净数据进行脑电节奏分解。锁相值(PLV)用于测量脑电电极的所有成对相位同步。然后对分解后的数据进行希尔伯特变换,提取瞬时相位。最后利用图论方法对泛函网络进行了量化。结果表明,与非目标刺激相比,目标刺激引发了更密集的神经活动。在执行古怪任务时,准确度较高的被试比准确度较低的被试有更大的神经活动。
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引用次数: 1
Ensuring Seamless Connectivity in Internet of Things: The Role of Low Power Lossy Networks 确保物联网的无缝连接:低功耗网络的作用
Pub Date : 2018-12-01 DOI: 10.1109/R10-HTC.2018.8629821
J. J, S. D. M. Kumar
The field of Information and Communication Technology (ICT) has witnessed a game changing development in the name of Internet of Things (IoT). The IoT paradigm attempts to connect everyday 'things' to the Internet. In order to realize various IoT applications like smart health, smart cities, and transportation; seamless connectivity among the IoT devices needs to be ensured. Routing in Low power Lossy Networks (LLNs) essentially contributes to providing the required connectivity. This paper throws light on the state-of-the-art research in LLN routing. Considering the current societal needs, various categories of routing protocols, such as proactive, on-demand, opportunistic, and cognitive routing protocols, have been reviewed and compared. Finally the paper lists major challenges, along with possible solutions, that need to be addressed immediately to realize various socially relevant IoT applications in its real sense.
信息通信技术(ICT)领域以物联网(IoT)的名义见证了一场颠覆性的发展。物联网范式试图将日常“事物”连接到互联网上。实现智能健康、智慧城市、交通等多种物联网应用;确保物联网设备之间的无缝连接。低功耗损耗网络(lln)中的路由本质上有助于提供所需的连接。本文介绍了LLN路由的最新研究进展。考虑到当前的社会需求,对各种类型的路由协议进行了回顾和比较,如主动路由协议、按需路由协议、机会路由协议和认知路由协议。最后,本文列出了需要立即解决的主要挑战以及可能的解决方案,以实现各种真正意义上的社会相关物联网应用。
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引用次数: 0
Road Navigation System Using Automatic Speech Recognition (ASR) And Natural Language Processing (NLP) 自动语音识别(ASR)和自然语言处理(NLP)的道路导航系统
Pub Date : 2018-12-01 DOI: 10.1109/R10-HTC.2018.8629859
Pooja Withanage, Tharaka Liyanage, Naditha Deeyakaduwe, Eshan Dias, S. Thelijjagoda
In a highly evolving technical era, Voice-based Navigation Systems play a major role to bridge the gap between human and machine. To overcome the difficulty in taking and understanding user's voice commands, simulating the natural language, process the route with user's turn by turn directions while mentioning key entities like street names, landmarks, point of interests, junctions and map the route in an interactive interface, we propose a user-centric roadmap navigation mobile application called “Direct Me”. The approach of generating the user preferred route, system will first convert the audio streams into text through Automatic Speech Recognizer (ASR) using Pocket Sphinx Library, followed by Natural Language Processing (NLP) by utilizing Stanford CoreNLP Framework to retrieve the navigation-associated information and process the route in the Map using Google Map API upon the user request. This system is used to provide an efficient approach to translate natural language directions to a machine-understandable format and will benefit the development of voice-based navigation-oriented humanmachine interface.
在一个高度发展的技术时代,语音导航系统在弥合人与机器之间的差距方面发挥着重要作用。为了克服用户语音指令难以理解和理解的问题,模拟自然语言,根据用户的转弯方向处理路线,同时提及街道名称、地标、兴趣点、路口等关键实体,并在交互界面中绘制路线,我们提出了一款以用户为中心的路线图导航移动应用“Direct Me”。在生成用户首选路线的方法上,系统首先使用Pocket Sphinx Library通过自动语音识别器(ASR)将音频流转换为文本,然后利用Stanford CoreNLP框架进行自然语言处理(NLP),检索导航相关信息,并根据用户请求使用谷歌Map API在地图中处理路线。该系统提供了一种将自然语言方向转换为机器可理解格式的有效方法,将有利于基于语音导航的人机界面的发展。
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引用次数: 7
Calculation of Dynamic Frequency Stability Margin in Islanded Microgrids 孤岛微电网动态频率稳定裕度计算
Pub Date : 2018-12-01 DOI: 10.1109/R10-HTC.2018.8629831
M. A. M. Manaz, Chan-nan Lu
Microgrid has the capability to maintain a reliable power supply during an emergency; microgrid technology is also suitable to deliver power to rural communities where providing power from the main grid is not economical. These microgrids can experience severe frequency variation due to their inherently low inertia. In this paper, we derive a closed-form formula to compute the dynamic frequency stability margin and propose a procedure to evaluate it using local measurements available in any location in the microgrid. The dynamic stability margin could be utilized to activate suitable responses from distributed energy resources during emergency situations to maintain frequency stability.
微电网有能力在紧急情况下保持可靠的电力供应;微电网技术也适用于向农村社区供电,因为从主电网供电并不经济。由于其固有的低惯性,这些微电网可能会经历严重的频率变化。在本文中,我们推导了一个计算动态频率稳定裕度的封闭公式,并提出了一个使用微电网中任何位置可用的局部测量来评估它的程序。动态稳定裕度可用于在紧急情况下激活分布式能源的适当响应,以保持频率稳定性。
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引用次数: 0
A Deep Neural Network Approach for Crop Selection and Yield Prediction in Bangladesh 孟加拉国作物选择和产量预测的深度神经网络方法
Pub Date : 2018-12-01 DOI: 10.1109/R10-HTC.2018.8629828
Tanhim Islam, Tanjir Alam Chisty, Amitabha Chakrabarty
Agriculture is the essential ingredients to mankind which is a major source of livelihood. Agriculture work in Bangladesh is mostly done in old ways which directly affects our economy. In addition, institutions of agriculture are working with manual data which cannot provide a proper solution for crop selection and yield prediction. This paper shows the best way of crop selection and yield prediction in minimum cost and effort. Artificial Neural Network is considered robust tools for modeling and prediction. This algorithm aims to get better output and prediction, as well as, support vector machine, Logistic Regression, and random forest algorithm is also considered in this study for comparing the accuracy and error rate. Moreover, all of these algorithms used here are just to see how well they performed for a dataset which is over 0.3 million. We have collected 46 parameters such as - maximum and minimum temperature, average rainfall, humidity, climate, weather, and types of land, types of chemical fertilizer, types of soil, soil structure, soil composition, soil moisture, soil consistency, soil reaction and soil texture for applying into this prediction process. In this paper, we have suggested using the deep neural network for agricultural crop selection and yield prediction.
农业是人类的重要组成部分,是人类主要的生计来源。孟加拉国的农业工作大多以旧方式完成,这直接影响到我们的经济。此外,农业机构正在使用人工数据,无法为作物选择和产量预测提供适当的解决方案。本文给出了以最小的成本和努力进行作物选择和产量预测的最佳方法。人工神经网络被认为是建模和预测的强大工具。该算法的目的是得到更好的输出和预测,为了比较准确率和错误率,本研究还考虑了支持向量机、逻辑回归和随机森林算法。此外,这里使用的所有这些算法只是为了看看它们在一个超过30万的数据集上表现得如何。我们收集了最高和最低温度、平均降雨量、湿度、气候、天气、土地类型、化肥类型、土壤类型、土壤结构、土壤成分、土壤水分、土壤稠度、土壤反应和土壤质地等46个参数用于预测过程。本文建议将深度神经网络应用于农作物选择和产量预测。
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引用次数: 28
Education and e-health for developing countries using NVIS communications 利用国家信息系统通信为发展中国家提供教育和电子保健服务
Pub Date : 2018-12-01 DOI: 10.1109/R10-HTC.2018.8629842
Joaquim Porte, J. Maso, J. Pijoan, Marta Miret, D. Badia, J. Jayasinghe
In this paper we present a new communications solution for remote villages in developing countries. The system is based in the Near Vertical Ionospheric Skywave (NVIS) technique, able to achieve coverage areas up to 250 Km without line of sight. It is a low-cost, low-power system that can be easily installed and put into operation. The radio system communicates with a smartphone, where a messaging app is running, so text and low resolution images can be sent without the need of any mobile operator. The system has been tested between one of the Andean communities of the Sacred Valley of Incas in Peru and Urubamba, the nearest city.
在本文中,我们为发展中国家的偏远村庄提出了一种新的通信解决方案。该系统基于近垂直电离层天波(NVIS)技术,能够在无视线的情况下覆盖250公里的区域。它是一种低成本、低功耗、易于安装和投入运行的系统。无线电系统与正在运行的信息应用程序的智能手机通信,因此无需任何移动运营商就可以发送文本和低分辨率图像。该系统已经在秘鲁印加圣谷的一个安第斯社区和最近的城市乌鲁班巴之间进行了测试。
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引用次数: 3
Sustainable Tourism: Application of Optimization Algorithms to Schedule Tour Plans 可持续旅游:优化算法在旅游计划安排中的应用
Pub Date : 2018-12-01 DOI: 10.1109/R10-HTC.2018.8629826
D. Perera, C. Rathnayaka, Sachin Dilan, Lasitha Siriweera, W. Rankothge
One of the challenging problems in the tourism industry is to maintain the environmental sustainability of the tourists attracted locations while giving a better user experience for the tourists. The proposed platform for sustainable tourism management system consist with following modules: A prediction module to predict an approximate value on tourist arrival for each location, an optimization algorithm module to decide the number of tourists that can be accommodated in each location considering the environmental sustainability, and an optimal path generating module to show the best route to each location. The optimization algorithm module is developed to decide the number of tourists for each location based on two approaches: Genetic Algorithms and Iterated Local Search. Next the optimal path generating module is developed based on traveling salesman problem.In this paper, the performances of the optimization algorithm module and the optimal path generating module is presented. Results show that, using the suggestions given by the algorithms help the tourist to enjoy a better experience in travelling while ensuring the sustainability in the tourism industry.
在为游客提供更好的用户体验的同时,保持吸引游客的地点的环境可持续性是旅游业面临的一个具有挑战性的问题。本文提出的可持续旅游管理系统平台包括以下几个模块:预测模块,用于预测每个地点的游客到达近似值;优化算法模块,用于考虑环境可持续性,确定每个地点可容纳的游客数量;最优路径生成模块,用于显示每个地点的最佳路线。优化算法模块基于遗传算法和迭代局部搜索两种方法确定每个地点的游客数量。其次,开发了基于旅行商问题的最优路径生成模块。本文介绍了优化算法模块和最优路径生成模块的性能。结果表明,利用算法给出的建议,在保证旅游业可持续发展的同时,可以帮助游客享受更好的旅游体验。
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引用次数: 8
期刊
2018 IEEE Region 10 Humanitarian Technology Conference (R10-HTC)
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